CAREER: Human Behavior Assessment from Internet Usage: Foundations, Applications and Algorithms

职业：基于互联网使用的人类行为评估：基础、应用程序和算法

• 批准号: 1559588
• 负责人: Sriram Chellappan
• 金额: $ 27.18万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-17 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1559588&HistoricalAwards=false
• 关键词: CAREER; Human; Behavior; Assessment; Internet

Human interaction with computers, and especially with the Internet, is ever increasing. As a consequence the field of cyber-psychology, which studies the thinking, behavior and attitudes of the person using the computer, is of growing importance. To date, studies in cyber-psychology have collected Internet usage data by means of self-reported surveys only, an approach which suffers from a number of drawbacks including human error, bias due to user concerns relating to social desirability, and limits on the volume and dimensionality of the data obtained. The PI's vision in this project is to advance human behavior assessment based on real Internet usage data, that is to say Internet usage data collected continuously, passively and unobtrusively without manual intervention while carefully maintaining user privacy expectations. To these ends, the PI will develop practical foundations, create two Internet enabled applications (one relating to online mental healthcare and the other to online socializing), and leverage results in behavioral psychology to design classification algorithms that demonstrate the ability to achieve significant insights and to detect behavioral similarities (relating to symptoms of depression and preferences in social contacts) based on Internet usage. The project builds on the PI's preliminary work that exploited real Internet usage data collected from Cisco NetFlow records to identify fine-grained Internet usage features associated with symptoms of depression, and will be executed with college students as primary subjects. The PI will collaborate in the current project with experts from the psychological and social sciences, clinical psychiatry, and the FBI's cyber crimes division. Outcomes will include an accurate characterization of Internet usage minimally affected by error and bias, and a large number of Internet usage features of high granularity for assessing human behavior, which together will yield insights and conclusions readily adaptable for practical utility.Broader Impacts: This research will advance our ability to assess human behavior based on Internet usage data. The online mental healthcare application will yield Internet enabled proactive, early and cost -effective mental health care to complement care in existing clinical settings, while the online socializing application will lead to improved online social experiences by leveraging mutual social preferences. Applications of the research to mitigating Internet fraud and detecting cyber bullying are immediate. The PI will collaborate with HBCU and RUI institutions as well as K-12 schools to further enhance project outreach.

人类与计算机，特别是与互联网的互动越来越多。 因此，研究使用计算机的人的思维、行为和态度的网络心理学领域变得越来越重要。 迄今为止，网络心理学研究仅通过自我报告的调查收集互联网使用数据，这种方法存在许多缺点，包括人为错误，由于用户对社会期望的关注而产生的偏见，以及所获得数据的数量和维度的限制。 PI在该项目中的愿景是基于真实的互联网使用数据推进人类行为评估，即在没有人工干预的情况下连续、被动和不引人注目地收集互联网使用数据，同时谨慎地维护用户隐私期望。 为此，PI将开发实用的基础，创建两个互联网应用程序（一个与在线精神保健有关，另一个与在线社交有关），并利用行为心理学的结果设计分类算法，以证明能够实现重要的见解并根据互联网使用情况检测行为相似性（与抑郁症状和社交偏好有关）。 该项目建立在PI的初步工作的基础上，利用从Cisco NetFlow记录中收集的真实的互联网使用数据来识别与抑郁症状相关的细粒度互联网使用特征，并将以大学生为主要对象执行。 PI将在当前项目中与来自心理和社会科学，临床精神病学以及FBI网络犯罪部门的专家合作。 结果将包括一个准确的描述互联网使用的影响最小的错误和偏见，以及大量的互联网使用的高粒度的特征，用于评估人类的行为，这将产生的见解和结论容易适应实际utility.Broader影响：这项研究将提高我们的能力，评估人类行为的基础上互联网使用数据。 在线精神卫生保健应用程序将产生互联网启用的主动、早期和具有成本效益的精神卫生保健，以补充现有临床环境中的护理，而在线社交应用程序将通过利用相互社交偏好来改善在线社交体验。 这项研究在减轻互联网欺诈和检测网络欺凌方面的应用是立即的。 PI将与HBCU和RUI机构以及K-12学校合作，进一步加强项目推广。